Bayesian statistical prediction analysis of gender imbalance in early age mortality

2022 ◽  
Author(s):  
K. Sudha ◽  
G. Venkatesan
Keyword(s):  
Statistical Prediction ◽  
Early Age ◽  
Gender Imbalance ◽  
Prediction Analysis

Statistical Prediction Analysis.

1978 ◽  
Vol 73 (361) ◽  
pp. 222
Author(s):  
Robert L. Winkler ◽  
J. Aitchison ◽  
I. R. Dunsmore
Keyword(s):  
Statistical Prediction ◽  
Prediction Analysis

scholarly journals Parents mention sons more often than daughters on social media

2019 ◽  
Vol 116 (6) ◽  
pp. 2039-2041 ◽  
Author(s):  
Elizaveta Sivak ◽  
Ivan Smirnov
Keyword(s):  
Social Media ◽  
Gender Inequality ◽  
Reproductive Behavior ◽  
Social Networking Site ◽  
Early Age ◽  
Gender Preference ◽  
Online Behavior ◽  
Gender Imbalance ◽  
Saint Petersburg ◽  
Gender Parity

Gender inequality starts early in life. Parents tend to prefer boys over girls, which is manifested in reproductive behavior, marital life, and parents’ pastimes and investments in their children. While social media and sharing information about children (so-called “sharenting”) have become an integral part of parenthood, whether and how gender preference shapes the online behavior of users are not well known. In this paper we use public posts made by 635,665 users from Saint Petersburg on a popular Russian social networking site, to investigate public mentions of daughters and sons on social media. We find that both men and women mention sons more often than daughters in their posts. We also find that posts featuring sons receive more “likes” on average. Our results indicate that girls are underrepresented in parents’ digital narratives about their children, in a country with an above-average ranking on gender parity. This gender imbalance may send a message that girls are less important than boys or that they deserve less attention, thus reinforcing gender inequality from an early age.

Statistical Prediction Analysis.

1978 ◽  
Vol 141 (1) ◽  
pp. 110
Author(s):  
Philip Dawid ◽  
J. Aitchison ◽  
I. R. Dunsmore
Keyword(s):  
Statistical Prediction ◽  
Prediction Analysis

Statistical Prediction Analysis

1981 ◽  
Vol 65 (431) ◽  
pp. 78
Author(s):  
Stanley Collings ◽  
J. Aitchison ◽  
I. R. Dunsmore
Keyword(s):  
Statistical Prediction ◽  
Prediction Analysis

A Community Based High Risk Register for Hearing Loss

1982 ◽  
Vol 47 (4) ◽  
pp. 373-375 ◽  
Author(s):  
James L. Fitch ◽  
Thomas F. Williams ◽  
Josephine E. Etienne
Keyword(s):  
Hearing Loss ◽  
System Identification ◽  
High Risk ◽  
Language Learning ◽  
Education Program ◽  
Communication System ◽  
Auditory Signal ◽  
Early Age ◽  
Community Based ◽  
Children With Hearing Loss

The critical need to identify children with hearing loss and provide treatment at the earliest possible age has become increasingly apparent in recent years (Northern & Downs, 1978). Reduction of the auditory signal during the critical language-learning period can severely limit the child's potential for developing a complete, effective communication system. Identification and treatment of children having handicapping conditions at an early age has gained impetus through the Handicapped Children's Early Education Program (HCEEP) projects funded by the Bureau of Education for the Handicapped (BEH).

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